gov.sandia.cognition.learning.algorithm.pca

Class AbstractPrincipalComponentsAnalysis

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.algorithm.pca.AbstractPrincipalComponentsAnalysis

All Implemented Interfaces:

BatchLearner<java.util.Collection<Vector>,PrincipalComponentsAnalysisFunction>, PrincipalComponentsAnalysis, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

ThinSingularValueDecomposition

@CodeReview(reviewer="Kevin R. Dixon",
            date="2008-07-23",
            changesNeeded=false,
            comments={"Minor change to javadoc.","Looks fine."})
public abstract class AbstractPrincipalComponentsAnalysis
extends AbstractCloneableSerializable
implements PrincipalComponentsAnalysis

Abstract implementation of PCA.

Since:

2.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AbstractPrincipalComponentsAnalysis(int numComponents, PrincipalComponentsAnalysisFunction result) Creates a new instance of AbstractPrincipalComponentsAnalysis

Method Summary

Modifier and Type	Method and Description
AbstractPrincipalComponentsAnalysis	clone() This makes public the clone method on the Object class and removes the exception that it throws.
int	getNumComponents() Gets the number of components used in the PCA dimension reduction.
PrincipalComponentsAnalysisFunction	getResult() Gets the VectorFunction that maps from the input space to the reduced output space of "getNumComponents" dimensions.
void	setNumComponents(int numComponents) Setter for numComponents
protected void	setResult(PrincipalComponentsAnalysisFunction result) Setter for result

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner

learn

Constructor Detail

AbstractPrincipalComponentsAnalysis

public AbstractPrincipalComponentsAnalysis(int numComponents,
                                           PrincipalComponentsAnalysisFunction result)

Creates a new instance of AbstractPrincipalComponentsAnalysis

Parameters:

numComponents - Number of components to extract from the data, must be greater than zero

result - Vector function that maps the input space onto a numComponents-dimension Vector representing the directions of maximal variance (information gain). The i-th row in the matrix approximates the i-th column of the "U" matrix of the Singular Value Decomposition.

Method Detail

clone

public AbstractPrincipalComponentsAnalysis clone()

Description copied from class: AbstractCloneableSerializable

This makes public the clone method on the Object class and removes the exception that it throws. Its default behavior is to automatically create a clone of the exact type of object that the clone is called on and to copy all primitives but to keep all references, which means it is a shallow copy. Extensions of this class may want to override this method (but call super.clone() to implement a "smart copy". That is, to target the most common use case for creating a copy of the object. Because of the default behavior being a shallow copy, extending classes only need to handle fields that need to have a deeper copy (or those that need to be reset). Some of the methods in ObjectUtil may be helpful in implementing a custom clone method. Note: The contract of this method is that you must use super.clone() as the basis for your implementation.

Specified by:

clone in interface CloneableSerializable

Overrides:

clone in class AbstractCloneableSerializable

Returns:

A clone of this object.

getNumComponents

public int getNumComponents()

Description copied from interface: PrincipalComponentsAnalysis

Gets the number of components used in the PCA dimension reduction.

Specified by:

getNumComponents in interface PrincipalComponentsAnalysis

Returns:

Number of components used in the PCA dimension reduction

setNumComponents

public void setNumComponents(int numComponents)

Setter for numComponents

Parameters:

numComponents - Number of components to extract from the data, must be greater than zero

getResult

public PrincipalComponentsAnalysisFunction getResult()

Description copied from interface: PrincipalComponentsAnalysis

Gets the VectorFunction that maps from the input space to the reduced output space of "getNumComponents" dimensions.

Specified by:

getResult in interface PrincipalComponentsAnalysis

Returns:

PCA function that reduces the dimensionality of the input space to a (hopefully) simpler and smaller output space

setResult

protected void setResult(PrincipalComponentsAnalysisFunction result)

Setter for result

Parameters:

result - Vector function that maps the input space onto a numComponents-dimension Vector representing the directions of maximal variance (information gain). The i-th row in the matrix approximates the i-th column of the "U" matrix of the Singular Value Decomposition.